Predicting Performance of Design-Build and Design-Bid-Build Projects Florence Yean Yng Ling 1 ; Swee Lean Chan 2 ; Edwin Chong 3 ; and Lee Ping Ee 4 Abstract: Design-build DB and design-bid-build DBB are two principal project delivery systems used in many countries. This paper reports on models constructed to predict performance of DB and DBB projects on 11 areas, using project-specific data collected from 87 building projects. The study included collecting, checking, and validating industry data, and the statistical development of multivariate linear regression models for predicting project performance. Robust models are developed to predict construction and delivery speeds of DB and DBB projects. Gross floor area of the project is the most significant factor affecting speed. Besides this, for DBB projects, contractors’ design ability, and adequacy of plant and equipment would ensure speedy completion of the projects. For DB projects, if the contract period is allowed to vary during tender evaluation, this would slow down the project. Robust models to predict turnover and system quality of DB projects are also constructed. A DB contractor’s track record is an important variable. They must have completed past projects to acceptable quality and have ability in financial, health and safety management. DOI: 10.1061/ASCE0733-93642004130:175 CE Database subject headings: Performance evaluation; Design/build; Project management; Models. Introduction The design-bid-build DBB procurement method is the prevalent procurement method in many countries such as Singapore, the U.K., and the United States. DBB is the traditional project deliv- ery system where the owner contracts separately with a designer and a constructor to design and construct the facility, respectively Mohsini and Davidson 1992. One of the alternative procurement systems is the design-build DB, whereby the owner contracts with a single entity to perform both design and construction under a single DB contract Janssens 1991. The objectives of this paper are 1 to find explanatory vari- ables that significantly affect project performance and 2 to con- struct models to predict the performance of DB and DBB projects. The first objective is important because contractors will know the important variables that they must pay very close atten- tion to in order that their projects can be completed within budget and schedule, to acceptable level of quality, and to the satisfaction of the owner and consultants. The second objective is important because the project performance models developed in this study can help owners, contractors, and architects and engineers A/Es predict what the likely project performance level will be. This is useful because based on the predicted project performance, own- ers and A/Es will be able to decide if they should use the DBB or DB procurement method in order to obtain the desired results. If they have already decided on a certain procurement method, the models will help them decide what the key variables which need to be controlled in order to obtain good project performance. Per- formance of a project is multifaceted. 11 possible performance measures are shown in Table 1, and grouped into four categories: cost, time, quality, and others. All the projects investigated in this study were based in Sin- gapore. They were all grass-root building construction projects i.e., not renovation works exceeding $5 million, and were com- pleted between 1993 and 2001. Both private and public sector projects were investigated. Literature Review In the U.K., Bennett et al. 1996 studied DB and DBB project selection and performance from the owners’ perspective. They constructed three models to predict unit cost, construction speed, and delivery speed, and obtained R 2 of 0.51, 0.90, and 0.80, re- spectively. The models were developed based on more than 170 projects. When trying to predict one performance metric example construction speed, the study included other performance metrics as predictor variables example quality and unit cost. This made the constructed model difficult to use, as the evaluator would not have the information of the other independent variables before the project starts. As can be seen from Table 1, there are many other performance metrics that were not reported in the Bennett et al. 1996 study. In the United States, Konchar and Sanvido 1998 conducted an empirical study that examined explanatory and interacting variables to predict project performance based on DB, DBB, and construction management at risk procurement systems. Using multivariate regression analysis, they developed models to predict 1 Assistant Professor, Dept. of Building, National Univ. of Singapore, 4 Architecture Dr., Singapore 117566 corresponding author. E-mail: bdglyy@nus.edu.sg 2 Assistant Professor, Dept. of Building, National Univ. of Singapore, 4 Architecture Dr., Singapore 117566. E-mail: bdgcsl@nus.edu.sg 3 Research Assistant, Dept. of Building, National Univ. of Singapore, 4 Architecture Dr., Singapore 117566. 4 Research Assistant, Dept. of Building, National Univ. of Singapore, 4 Architecture Dr., Singapore 117566. Note. Discussion open until July 1, 2004. Separate discussions must be submitted for individual papers. To extend the closing date by one month, a written request must be filed with the ASCE Managing Editor. The manuscript for this paper was submitted for review and possible publication on May 15, 2002; approved on November 7, 2002. This paper is part of the Journal of Construction Engineering and Management, Vol. 130, No. 1, February 1, 2004. ©ASCE, ISSN 0733-9364/2004/1- 75– 83/$18.00. JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT © ASCE / JANUARY/FEBRUARY 2004 / 75 J. Constr. Eng. Manage., 2004, 130(1): 75-83 Downloaded from ascelibrary.org by CASA Institution Identity on 04/20/19. Copyright ASCE. For personal use only; all rights reserved.